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A New Indexing Method for Approximate Search in Text Databases

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2 Author(s)
Fei Shi ; Comput. Sci. Dept., Suffolk Univ., Boston, MA ; Mefford, C.

We present an index structure to support the approximate keyword search in text databases. In an approximate keyword search query, the user presents a query word Q and a tolerance value k (kges0), and wishes to find all documents in the database that contain the query word Q or any other word in the vocabulary that matches Q approximately (We say that two words match each other approximately if the edit distance between them does not exceed the tolerance value k. In a typical text database application, a user chooses k=1, 2, 3, or 4). Our index structure is built on the underlying vocabulary of the text database. The new technique has two principal components - a new data structure called the V-tree and its partition methods for clustering words in the vocabulary into subgroups. We have implemented our index structure and conducted experiments on real-world data. Our experiments show that even for very large text database, the construction of our index and a search for keywords that match the query word approximately can be done quickly. Our implementation makes it clear that the V-tree data structure can be easily integrated into existing access structures built on the database such as the inverted index file

Published in:

Computer and Information Technology, 2005. CIT 2005. The Fifth International Conference on

Date of Conference:

21-23 Sept. 2005

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